4 papers
AR as an Evaluation Playground: Bridging Metrics and Visual Perception of Computer Vision Models
Ashkan Ganj, Yiqin Zhao, Tian Guo
Quantitative metrics are central to evaluating computer vision (CV) models, but they often fail to capture real-world performance due to protocol inconsistencies and ground-truth n…
HybridDepth: Robust Metric Depth Fusion by Leveraging Depth from Focus and Single-Image Priors
Ashkan Ganj, Hang Su, Tian Guo
We propose HYBRIDDEPTH, a robust depth estimation pipeline that addresses key challenges in depth estimation,including scale ambiguity, hardware heterogeneity, and generalizability…
Mobile AR Depth Estimation: Challenges & Prospects -- Extended Version
Ashkan Ganj, Yiqin Zhao, Hang Su +1
Metric depth estimation plays an important role in mobile augmented reality (AR). With accurate metric depth, we can achieve more realistic user interactions such as object placeme…
Get-A-Sense: Designing Spatial Context Awareness for Mobile AR Environment Understanding
Yiqin Zhao, Ashkan Ganj, Tian Guo
Physical environment understanding is vital in delivering immersive and interactive mobile augmented reality (AR) user experiences. Recently, we have witnessed a transition in the…